About: An Image Registration-Based Method for EPI Distortion Correction Based on Opposite Phase Encoding (COPE)

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	An Image Registration-Based Method for EPI Distortion Correction Based on Opposite Phase Encoding (COPE)
Creator	Ashburner, John Bastiani, Matteo Breman, Hester Eck, Judith Fritz, Levin Goebel, Rainer Mulders, Joost Peters, Judith Pyles, John Roebroeck, Alard Breman, H Fritz, L Mulders, J
Source	PMC
abstract	Surprisingly, estimated voxel displacement maps (VDMs), based on image registration, seem to work just as well to correct geometrical distortion in functional MRI data (EPI) as VDMs based on actual information about the magnetic field. In this article, we compare our new image registration-based distortion correction method ‘COPE’ to an implementation of the pixelshift method. Our approach builds on existing image registration-based techniques using opposite phase encoding, extending these by local cost aggregation. Comparison of these methods with 3T and 7T spin-echo (SE) and gradient-echo (GE) data show that the image registration-based method is a good alternative to the fieldmap-based EPI distortion correction method.
has issue date	2020-05-13(xsd:dateTime)
bibo:doi	10.1007/978-3-030-50120-4_12
has license	no-cc
sha1sum (hex)	c15a64529b0567451f754416d860aab405fb7748
schema:url	https://doi.org/10.1007/978-3-030-50120-4_12
resource representing a document's title	An Image Registration-Based Method for EPI Distortion Correction Based on Opposite Phase Encoding (COPE)
has PubMed Central identifier	PMC7279930
schema:publication	Biomedical Image Registration
resource representing a document's body	covid:c15a64529b0567451f754416d860aab405fb7748#body_text
is schema:about of	named entity 'geometrical' named entity 'good' named entity 'WORK' named entity 'JUST' named entity 'GOOD' named entity 'IS A' named entity 'IMAGE REGISTRATION' named entity 'FUNCTIONAL MRI' named entity 'AGGREGATION' named entity 'functional MRI' named entity 'data' named entity 'distortion' named entity 'image registration' named entity 'VDMs' named entity 'VDMs' named entity 'EPI' named entity 'image registration' named entity 'Phase Encoding' named entity 'Distortion' named entity 'gradient echo' named entity 'anatomical space' named entity 'geometric distortion' named entity 'Gauss-Newton' named entity 'v1.1' named entity 'displacement map' named entity 'University of Maastricht' named entity 'BrainVoyager' named entity 'displacement map' named entity 'Nemenyi test' named entity 'BrainVoyager' named entity 'BOLD' named entity 'high pass filter' named entity '1.6' named entity 'image registration' named entity 'voxel' named entity 'B0 field' named entity 'multigrid' named entity 'BrainVoyager' named entity 'non-parametric test' named entity 'Netherlands' named entity 'High Sierra' named entity 'Maastricht' named entity 'BOLD' named entity 'local search' named entity 'spin echo' named entity 'Netherlands' named entity 'Pittsburgh' named entity 'image registration' named entity 'image registration' named entity 'gradient echo' named entity 'Germany' named entity 'BrainVoyager' named entity 'Siemens' named entity 'image registration' named entity 'Maastricht' named entity 'GHz' named entity 'voxels' named entity 'interpolation' named entity 'Gauss-Newton' named entity 'voxel' named entity 'echo time' named entity 'diffusion' named entity 'MHz' named entity 'BrainVoyager' named entity 'macOS' named entity 'gradient' named entity 'Fourier domain' named entity 'SSD' named entity 'matrices' named entity 'complex conjugate' named entity 'crosscorrelation'

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